{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "42a5d119",
   "metadata": {},
   "source": [
    "# 数据分析基本流程"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e02b02e",
   "metadata": {},
   "source": [
    "- 明确目的\n",
    "    - 分析客户最喜欢的菜\n",
    "    - 分析餐馆的毛收益\n",
    "- 数据获取\n",
    "    - Excel文档已获取\n",
    "- 数据处理\n",
    "- 数据分析\n",
    "    - pandas聚合函数\n",
    "    - 机器学习的算法：分类、回归、降维\n",
    "- 结果呈现\n",
    "- 数据应用"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "7de42170",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-04T11:49:52.782859800Z",
     "start_time": "2023-08-04T11:49:52.715041500Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8cf8a6a5",
   "metadata": {},
   "source": [
    "## 加载数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "93f20d11",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-04T11:49:54.608391200Z",
     "start_time": "2023-08-04T11:49:52.724018300Z"
    }
   },
   "outputs": [],
   "source": [
    "data1 = pd.read_excel('meal_order_detail.xlsx', sheet_name='meal_order_detail1')\n",
    "data2 = pd.read_excel('meal_order_detail.xlsx', sheet_name='meal_order_detail2')\n",
    "data3 = pd.read_excel('meal_order_detail.xlsx', sheet_name='meal_order_detail3')"
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "## 数据预处理"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "f7023081-18d5-4416-93a5-e41e0cd37e89",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-08-04T11:49:54.624348100Z",
     "start_time": "2023-08-04T11:49:54.610386700Z"
    }
   },
   "outputs": [],
   "source": [
    "# 数据合并处理\n",
    "data = pd.concat([data1, data2, data3], axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "outputs": [],
   "source": [
    "# 数据缺省处理\n",
    "data.dropna(axis=1, inplace=True)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-04T11:49:54.653410700Z",
     "start_time": "2023-08-04T11:49:54.626343800Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "outputs": [
    {
     "data": {
      "text/plain": "   detail_id  order_id  dishes_id dishes_name  itemis_add  counts  amounts  \\\n0       2956       417     610062        蒜蓉生蚝           0       1       49   \n1       2958       417     609957       蒙古烤羊腿           0       1       48   \n2       2961       417     609950        大蒜苋菜           0       1       30   \n3       2966       417     610038       芝麻烤紫菜           0       1       25   \n4       2968       417     610003         蒜香包           0       1       13   \n\n     place_order_time  add_inprice      picture_file  emp_id  \n0 2016-08-01 11:05:36            0  caipu/104001.jpg    1442  \n1 2016-08-01 11:07:07            0  caipu/202003.jpg    1442  \n2 2016-08-01 11:07:40            0  caipu/303001.jpg    1442  \n3 2016-08-01 11:11:11            0  caipu/105002.jpg    1442  \n4 2016-08-01 11:11:30            0  caipu/503002.jpg    1442  ",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>detail_id</th>\n      <th>order_id</th>\n      <th>dishes_id</th>\n      <th>dishes_name</th>\n      <th>itemis_add</th>\n      <th>counts</th>\n      <th>amounts</th>\n      <th>place_order_time</th>\n      <th>add_inprice</th>\n      <th>picture_file</th>\n      <th>emp_id</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2956</td>\n      <td>417</td>\n      <td>610062</td>\n      <td>蒜蓉生蚝</td>\n      <td>0</td>\n      <td>1</td>\n      <td>49</td>\n      <td>2016-08-01 11:05:36</td>\n      <td>0</td>\n      <td>caipu/104001.jpg</td>\n      <td>1442</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2958</td>\n      <td>417</td>\n      <td>609957</td>\n      <td>蒙古烤羊腿</td>\n      <td>0</td>\n      <td>1</td>\n      <td>48</td>\n      <td>2016-08-01 11:07:07</td>\n      <td>0</td>\n      <td>caipu/202003.jpg</td>\n      <td>1442</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2961</td>\n      <td>417</td>\n      <td>609950</td>\n      <td>大蒜苋菜</td>\n      <td>0</td>\n      <td>1</td>\n      <td>30</td>\n      <td>2016-08-01 11:07:40</td>\n      <td>0</td>\n      <td>caipu/303001.jpg</td>\n      <td>1442</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2966</td>\n      <td>417</td>\n      <td>610038</td>\n      <td>芝麻烤紫菜</td>\n      <td>0</td>\n      <td>1</td>\n      <td>25</td>\n      <td>2016-08-01 11:11:11</td>\n      <td>0</td>\n      <td>caipu/105002.jpg</td>\n      <td>1442</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2968</td>\n      <td>417</td>\n      <td>610003</td>\n      <td>蒜香包</td>\n      <td>0</td>\n      <td>1</td>\n      <td>13</td>\n      <td>2016-08-01 11:11:30</td>\n      <td>0</td>\n      <td>caipu/503002.jpg</td>\n      <td>1442</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-04T11:49:54.657400600Z",
     "start_time": "2023-08-04T11:49:54.641442300Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 10037 entries, 0 to 3610\n",
      "Data columns (total 11 columns):\n",
      " #   Column            Non-Null Count  Dtype         \n",
      "---  ------            --------------  -----         \n",
      " 0   detail_id         10037 non-null  int64         \n",
      " 1   order_id          10037 non-null  int64         \n",
      " 2   dishes_id         10037 non-null  int64         \n",
      " 3   dishes_name       10037 non-null  object        \n",
      " 4   itemis_add        10037 non-null  int64         \n",
      " 5   counts            10037 non-null  int64         \n",
      " 6   amounts           10037 non-null  int64         \n",
      " 7   place_order_time  10037 non-null  datetime64[ns]\n",
      " 8   add_inprice       10037 non-null  int64         \n",
      " 9   picture_file      10037 non-null  object        \n",
      " 10  emp_id            10037 non-null  int64         \n",
      "dtypes: datetime64[ns](1), int64(8), object(2)\n",
      "memory usage: 941.0+ KB\n"
     ]
    }
   ],
   "source": [
    "# 查看df信息\n",
    "data.info()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-04T11:49:54.671366800Z",
     "start_time": "2023-08-04T11:49:54.657400600Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "## 数据分析"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "### 菜品平均价格"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "outputs": [
    {
     "data": {
      "text/plain": "44.82"
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pandas的求平均值的方法\n",
    "round(data['amounts'].mean(), 2)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-04T11:49:54.732217600Z",
     "start_time": "2023-08-04T11:49:54.672364900Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "outputs": [
    {
     "data": {
      "text/plain": "44.82"
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# numpy的求平均值函数\n",
    "value = np.mean(data['amounts'])\n",
    "round(value, 2)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-04T11:49:54.766142900Z",
     "start_time": "2023-08-04T11:49:54.689333900Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "outputs": [],
   "source": [
    "arr = np.random.randint(0, 10, size=(3,4))"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-04T11:49:54.781114600Z",
     "start_time": "2023-08-04T11:49:54.706287700Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[6 4 4 5]\n",
      " [2 8 6 4]\n",
      " [0 5 3 6]]\n"
     ]
    }
   ],
   "source": [
    "print(arr)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-04T11:49:54.782111600Z",
     "start_time": "2023-08-04T11:49:54.724239700Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2.66666667 5.66666667 4.33333333 5.        ]\n"
     ]
    }
   ],
   "source": [
    "print(arr.mean(axis=0))"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-04T11:49:54.822005Z",
     "start_time": "2023-08-04T11:49:54.738201900Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[4.75 5.   3.5 ]\n"
     ]
    }
   ],
   "source": [
    "print(arr.mean(axis=1))"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-04T11:49:54.885834800Z",
     "start_time": "2023-08-04T11:49:54.753162500Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "### 最喜欢的菜"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "outputs": [
    {
     "data": {
      "text/plain": "白饭/大碗               323\n凉拌菠菜                269\n谷稻小庄                239\n麻辣小龙虾               216\n辣炒鱿鱼                189\n                   ... \n红酒土豆烧鸭腿\\r\\n           3\n五香酱驴肉\\r\\n             2\n张裕葡萄酒张裕赤霞珠干红\\r\\n      2\n蒙古烤羊腿                 1\n香辣爆羊肝\\r\\n             1\nName: dishes_name, Length: 158, dtype: int64"
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['dishes_name'].value_counts()"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-04T11:49:54.924729800Z",
     "start_time": "2023-08-04T11:49:54.769135400Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "outputs": [],
   "source": [
    "dishes_count = data['dishes_name'].value_counts()[:10]"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-04T11:49:54.928719500Z",
     "start_time": "2023-08-04T11:49:54.798069100Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "outputs": [
    {
     "data": {
      "text/plain": "白饭/大碗        323\n凉拌菠菜         269\n谷稻小庄         239\n麻辣小龙虾        216\n辣炒鱿鱼         189\n芝士烩波士顿龙虾     188\n五色糯米饭(七色)    187\n白饭/小碗        186\n香酥两吃大虾       178\n焖猪手          173\nName: dishes_name, dtype: int64"
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dishes_count"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-04T11:49:54.929717600Z",
     "start_time": "2023-08-04T11:49:54.801061700Z"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "# 数据可视化"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "outputs": [
    {
     "data": {
      "text/plain": "<AxesSubplot:>"
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 指定字体\n",
    "plt.rcParams['font.sans-serif'] = 'SimHei'\n",
    "# 1、方法一：df,series有一个plot()方法。可以绘图\n",
    "dishes_count.plot(kind='bar')"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-04T11:49:54.968613600Z",
     "start_time": "2023-08-04T11:49:54.817019300Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "outputs": [
    {
     "data": {
      "text/plain": "<AxesSubplot:>"
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dishes_count.plot(kind='line', fontsize='18', color=['r'])\n",
    "dishes_count.plot(kind='bar')"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-04T11:49:55.169230100Z",
     "start_time": "2023-08-04T11:49:54.945674800Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[323 269 239 216 189 188 187 186 178 173]\n"
     ]
    }
   ],
   "source": [
    "print(dishes_count.values)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-04T11:49:55.238045200Z",
     "start_time": "2023-08-04T11:49:55.161252Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dishes_count.plot(kind='line', fontsize='18', color=['r'])\n",
    "dishes_count.plot(kind='bar')\n",
    "for x, y in enumerate(dishes_count.values):\n",
    "    plt.text(x, y+5, y, ha='center')"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-04T11:49:55.347752400Z",
     "start_time": "2023-08-04T11:49:55.180201200Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "outputs": [
    {
     "data": {
      "text/plain": "<AxesSubplot:ylabel='dishes_name'>"
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dishes_count.plot(kind='pie', fontsize='16')"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-04T11:49:55.444494500Z",
     "start_time": "2023-08-04T11:49:55.334788300Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-08-04T11:49:55.470424400Z",
     "start_time": "2023-08-04T11:49:55.445491500Z"
    }
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.7"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
